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Get rid of eval statements by using indirect indexing of structures

time-shift
Johannes Pfeifer 2015-10-12 15:20:15 +02:00
parent b7cbb563d6
commit 7ebbc41d8a
6 changed files with 81 additions and 83 deletions
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2
matlab/GetPosteriorParametersStatistics.m
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@ -389,6 +389,6 @@ oo.posterior_density.(type).(name) = density;
function [post_mean,hpd_interval,post_var] = Extractoo(oo,name,type)
hpd_interval = zeros(2,1);
post_mean = oo.posterior_mean.(type).(name);
hpd_interval(1) = oo.posterior_hpdinf.(type).(name);
hpd_interval(1) = oo.posterior_hpdinf.(type).(name);
hpd_interval(2) = oo.posterior_hpdsup.(type).(name);
post_var = oo.posterior_variance.(type).(name);

24
matlab/PosteriorIRF.m
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@ -304,12 +304,12 @@ clear STOCK_IRF_DSGE;
for i = irf_shocks_indx
for j = 1:nvar
name = [deblank(M_.endo_names(IndxVariables(j),:)) '_' deblank(tit(i,:))];
eval(['oo_.PosteriorIRF.dsge.Mean.' name ' = MeanIRF(:,j,i);']);
eval(['oo_.PosteriorIRF.dsge.Median.' name ' = MedianIRF(:,j,i);']);
eval(['oo_.PosteriorIRF.dsge.Var.' name ' = VarIRF(:,j,i);']);
eval(['oo_.PosteriorIRF.dsge.deciles.' name ' = DistribIRF(:,:,j,i);']);
eval(['oo_.PosteriorIRF.dsge.HPDinf.' name ' = HPDIRF(:,1,j,i);']);
eval(['oo_.PosteriorIRF.dsge.HPDsup.' name ' = HPDIRF(:,2,j,i);']);
oo_.PosteriorIRF.dsge.Mean.(name) = MeanIRF(:,j,i);
oo_.PosteriorIRF.dsge.Median.(name) = MedianIRF(:,j,i);
oo_.PosteriorIRF.dsge.Var.(name) = VarIRF(:,j,i);
oo_.PosteriorIRF.dsge.deciles.(name) = DistribIRF(:,:,j,i);
oo_.PosteriorIRF.dsge.HPDinf.(name) = HPDIRF(:,1,j,i);
oo_.PosteriorIRF.dsge.HPDsup.(name) = HPDIRF(:,2,j,i);
end
end
@ -341,12 +341,12 @@ if MAX_nirfs_dsgevar
for i = irf_shocks_indx
for j = 1:nvar
name = [deblank(M_.endo_names(IndxVariables(j),:)) '_' deblank(tit(i,:))];
eval(['oo_.PosteriorIRF.bvardsge.Mean.' name ' = MeanIRFdsgevar(:,j,i);']);
eval(['oo_.PosteriorIRF.bvardsge.Median.' name ' = MedianIRFdsgevar(:,j,i);']);
eval(['oo_.PosteriorIRF.bvardsge.Var.' name ' = VarIRFdsgevar(:,j,i);']);
eval(['oo_.PosteriorIRF.bvardsge.deciles.' name ' = DistribIRFdsgevar(:,:,j,i);']);
eval(['oo_.PosteriorIRF.bvardsge.HPDinf.' name ' = HPDIRFdsgevar(:,1,j,i);']);
eval(['oo_.PosteriorIRF.bvardsge.HPDsup.' name ' = HPDIRFdsgevar(:,2,j,i);']);
oo_.PosteriorIRF.bvardsge.Mean.(name) = MeanIRFdsgevar(:,j,i);
oo_.PosteriorIRF.bvardsge.Median.(name) = MedianIRFdsgevar(:,j,i);
oo_.PosteriorIRF.bvardsge.Var.(name) = VarIRFdsgevar(:,j,i);
oo_.PosteriorIRF.bvardsge.deciles.(name) = DistribIRFdsgevar(:,:,j,i);
oo_.PosteriorIRF.bvardsge.HPDinf.(name) = HPDIRFdsgevar(:,1,j,i);
oo_.PosteriorIRF.bvardsge.HPDsup.(name) = HPDIRFdsgevar(:,2,j,i);
end
end
end

22
matlab/conditional_variance_decomposition_mc_analysis.m
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@ -62,11 +62,11 @@ end
name = [ var_list(endogenous_variable_index,:) '.' exo ];
if isfield(oo_, [ TYPE 'TheoreticalMoments' ])
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])
temporary_structure = oo_.([TYPE 'TheoreticalMoments']);
if isfield(temporary_structure,'dsge')
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
temporary_structure = oo_.([TYPE 'TheoreticalMoments']).dsge;
if isfield(temporary_structure,'ConditionalVarianceDecomposition')
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Mean;'])
temporary_structure = oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.Mean;
if isfield(temporary_structure,name)
if sum(Steps-temporary_structure.(name)(1,:)) == 0
% Nothing (new) to do here...
@ -112,13 +112,13 @@ for i=1:length(Steps)
p_hpdinf(i) = hpd_interval(1);
p_hpdsup(i) = hpd_interval(2);
end
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Steps = Steps;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Mean.' name ' = p_mean;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Median.' name ' = p_median;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.Variance.' name ' = p_variance;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.HPDinf.' name ' = p_hpdinf;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.HPDsup.' name ' = p_hpdsup;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.deciles.' name ' = p_deciles;']);
oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.Steps = Steps;
oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.Mean.(name) = p_mean;
oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.Median.(name) = p_median;
oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.Variance.(name) = p_variance;
oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.HPDinf.(name) = p_hpdinf;
oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.HPDsup.(name) = p_hpdsup;
oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.deciles.(name) = p_deciles;
if options_.estimation.moments_posterior_density.indicator
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.ConditionalVarianceDecomposition.density.' name ' = p_density;']);
oo_.([TYPE 'TheoreticalMoments']).dsge.ConditionalVarianceDecomposition.density.(name) = p_density;
end

42
matlab/correlation_mc_analysis.m
View File

@ -44,15 +44,15 @@ else
end
if isfield(oo_,[TYPE 'TheoreticalMoments'])
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])
temporary_structure = oo_.([TYPE, 'TheoreticalMoments']);
if isfield(temporary_structure,'dsge')
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
temporary_structure = oo_.([TYPE, 'TheoreticalMoments']).dsge;
if isfield(temporary_structure,'correlation')
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.correlation.Mean;'])
temporary_structure = oo_.([TYPE, 'TheoreticalMoments']).dsge.correlation.Mean;
if isfield(temporary_structure,deblank(var1))
eval(['temporary_structure_1 = oo_.' TYPE 'TheoreticalMoments.dsge.correlation.Mean.' var1 ';'])
temporary_structure_1 = oo_.([TYPE, 'TheoreticalMoments']).dsge.correlation.Mean.(var1);
if isfield(temporary_structure_1,deblank(var2))
eval(['temporary_structure_2 = temporary_structure_1.' var2 ';'])
temporary_structure_2 = temporary_structure_1.(var2);
l1 = length(temporary_structure_2);
if l1<nar
% INITIALIZATION:
@ -99,9 +99,9 @@ if ~isconst(tmp)
posterior_moments(tmp,0,mh_conf_sig);
end
if isfield(oo_,[ TYPE 'TheoreticalMoments'])
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])
temporary_structure = oo_.([TYPE, 'TheoreticalMoments']);
if isfield(temporary_structure,'dsge')
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
temporary_structure = oo_.([TYPE, 'TheoreticalMoments']).dsge;
if isfield(temporary_structure,'correlation')
oo_ = fill_output_structure(var1,var2,TYPE,oo_,'Mean',nar,p_mean);
oo_ = fill_output_structure(var1,var2,TYPE,oo_,'Median',nar,p_median);
@ -117,9 +117,9 @@ if ~isconst(tmp)
end
else
if isfield(oo_,'PosteriorTheoreticalMoments')
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])
temporary_structure = oo_.([TYPE, 'TheoreticalMoments']);
if isfield(temporary_structure,'dsge')
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
temporary_structure = oo_.([TYPE, 'TheoreticalMoments']).dsge;
if isfield(temporary_structure,'correlation')
oo_ = fill_output_structure(var1,var2,TYPE,oo_,'Mean',nar,NaN);
oo_ = fill_output_structure(var1,var2,TYPE,oo_,'Median',nar,NaN);
@ -136,30 +136,28 @@ else
end
function oo_ = initialize_output_structure(var1,var2,nar,type,oo_,options_)
name = [ var1 '.' var2 ];
eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.Mean.' name ' = NaN(' int2str(nar) ',1);']);
eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.Median.' name ' = NaN(' int2str(nar) ',1);']);
eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.Variance.' name ' = NaN(' int2str(nar) ',1);']);
eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.HPDinf.' name ' = NaN(' int2str(nar) ',1);']);
eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.HPDsup.' name ' = NaN(' int2str(nar) ',1);']);
eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.deciles.' name ' = cell(' int2str(nar) ',1);']);
oo_.([type, 'TheoreticalMoments']).dsge.correlation.Mean.(var1).(var2) = NaN(nar,1);
oo_.([type, 'TheoreticalMoments']).dsge.correlation.Median.(var1).(var2) = NaN(nar,1);
oo_.([type, 'TheoreticalMoments']).dsge.correlation.Variance.(var1).(var2) = NaN(nar,1);
oo_.([type, 'TheoreticalMoments']).dsge.correlation.HPDinf.(var1).(var2) = NaN(nar,1);
oo_.([type, 'TheoreticalMoments']).dsge.correlation.HPDsup.(var1).(var2) = NaN(nar,1);
oo_.([type, 'TheoreticalMoments']).dsge.correlation.deciles.(var1).(var2) = cell(nar,1);
if options_.estimation.moments_posterior_density.indicator
eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.density.' name ' = cell(' int2str(nar) ',1);']);
oo_.([type, 'TheoreticalMoments']).dsge.correlation.density.(var1).(var2) = cell(nar,1);
end
for i=1:nar
if options_.estimation.moments_posterior_density.indicator
eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.density.' name '(' int2str(i) ',1) = {NaN};']);
oo_.([type, 'TheoreticalMoments']).dsge.correlation.density.(var1).(var2)(i,1) = {NaN};
end
eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.deciles.' name '(' int2str(i) ',1) = {NaN};']);
oo_.([type, 'TheoreticalMoments']).dsge.correlation.deciles.(var1).(var2)(i,1) = {NaN};
end
function oo_ = fill_output_structure(var1,var2,type,oo_,moment,lag,result)
name = [ var1 '.' var2 ];
switch moment
case {'Mean','Median','Variance','HPDinf','HPDsup'}
eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.' moment '.' name '(' int2str(lag) ',1) = result;']);
oo_.([type, 'TheoreticalMoments']).dsge.correlation.(moment).(var1).(var2)(lag,1) = result;
case {'deciles','density'}
eval(['oo_.' type 'TheoreticalMoments.dsge.correlation.' moment '.' name '(' int2str(lag) ',1) = {result};']);
oo_.([type, 'TheoreticalMoments']).dsge.correlation.(moment).(var1).(var2)(lag,1) = {result};
otherwise
disp('fill_output_structure:: Unknown field!')
end

54
matlab/covariance_mc_analysis.m
View File

@ -61,20 +61,20 @@ else
end
if isfield(oo_,[ TYPE 'TheoreticalMoments'])
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])
temporary_structure = oo_.([TYPE, 'TheoreticalMoments']);
if isfield(temporary_structure,'dsge')
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
temporary_structure = oo_.([TYPE, 'TheoreticalMoments']).dsge;
if isfield(temporary_structure,'covariance')
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.covariance.Mean;'])
temporary_structure = oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Mean;
if isfield(temporary_structure,var1)
eval(['temporary_structure_1 = oo_.' TYPE 'TheoreticalMoments.dsge.covariance.Mean.' var1 ';'])
temporary_structure_1 = oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Mean.(var1);
if isfield(temporary_structure_1,var2)
% Nothing to do (the covariance matrix is symmetric!).
return
end
else
if isfield(temporary_structure,var2)
eval(['temporary_structure_2 = oo_.' TYPE 'TheoreticalMoments.dsge.covariance.Mean.' var2 ';'])
temporary_structure_2 = oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Mean.(var2);
if isfield(temporary_structure_2,var1)
% Nothing to do (the covariance matrix is symmetric!).
return
@ -104,31 +104,31 @@ for file = 1:length(ListOfFiles)
end
i1 = i2+1;
end
name = [var1 '.' var2];
if ~isconst(tmp)
if options_.estimation.moments_posterior_density.indicator
[p_mean, p_median, p_var, hpd_interval, p_deciles, density] = ...
posterior_moments(tmp,1,mh_conf_sig);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.density.' name ' = density;']);
oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.density.(var1).(var2) = density;
else
[p_mean, p_median, p_var, hpd_interval, p_deciles] = ...
posterior_moments(tmp,0,mh_conf_sig);
end
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.Mean.' name ' = p_mean;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.Median.' name ' = p_median;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.Variance.' name ' = p_var;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.HPDinf.' name ' = hpd_interval(1);']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.HPDsup.' name ' = hpd_interval(2);']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.deciles.' name ' = p_deciles;']);
oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Mean.(var1).(var2) = p_mean;
oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Median.(var1).(var2) = p_median;
oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Variance.(var1).(var2) = p_var;
oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.HPDinf.(var1).(var2) = hpd_interval(1);
oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.HPDsup.(var1).(var2) = hpd_interval(2);
oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.deciles.(var1).(var2) = p_deciles;
else
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.Mean.' name ' = NaN;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.Median.' name ' = NaN;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.Variance.' name ' = NaN;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.HPDinf.' name ' = NaN;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.HPDsup.' name ' = NaN;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.deciles.' name ' = NaN;']);
oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Mean.(var1).(var2) = NaN;
oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Median.(var1).(var2) = NaN;
oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.Variance.(var1).(var2) = NaN;
oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.HPDinf.(var1).(var2) = NaN;
oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.HPDsup.(var1).(var2) = NaN;
oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.deciles.(var1).(var2) = NaN;
if options_.estimation.moments_posterior_density.indicator
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.covariance.density.' name ' = NaN;']);
oo_.([TYPE, 'TheoreticalMoments']).dsge.covariance.density.(var1).(var2) = NaN;
end
end
@ -136,15 +136,15 @@ if options_.contemporaneous_correlation
if options_.estimation.moments_posterior_density.indicator
[p_mean, p_median, p_var, hpd_interval, p_deciles, density] = ...
posterior_moments(tmp_corr_mat,1,mh_conf_sig);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.contemporeaneous_correlation.density.' name ' = density;']);
oo_.([TYPE, 'TheoreticalMoments']).dsge.contemporeaneous_correlation.density.(var1).(var2) = density;
else
[p_mean, p_median, p_var, hpd_interval, p_deciles] = ...
posterior_moments(tmp_corr_mat,0,mh_conf_sig);
end
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.contemporeaneous_correlation.Mean.' name ' = p_mean;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.contemporeaneous_correlation.Median.' name ' = p_median;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.contemporeaneous_correlation.Variance.' name ' = p_var;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.contemporeaneous_correlation.HPDinf.' name ' = hpd_interval(1);']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.contemporeaneous_correlation.HPDsup.' name ' = hpd_interval(2);']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.contemporeaneous_correlation.deciles.' name ' = p_deciles;']);
oo_.([TYPE, 'TheoreticalMoments']).dsge.contemporeaneous_correlation.Mean.(var1).(var2) = p_mean;
oo_.([TYPE, 'TheoreticalMoments']).dsge.contemporeaneous_correlation.Median.(var1).(var2) = p_median;
oo_.([TYPE, 'TheoreticalMoments']).dsge.contemporeaneous_correlation.Variance.(var1).(var2) = p_var;
oo_.([TYPE, 'TheoreticalMoments']).dsge.contemporeaneous_correlation.HPDinf.(var1).(var2) = hpd_interval(1);
oo_.([TYPE, 'TheoreticalMoments']).dsge.contemporeaneous_correlation.HPDsup.(var1).(var2) = hpd_interval(2);
oo_.([TYPE, 'TheoreticalMoments']).dsge.contemporeaneous_correlation.deciles.(var1).(var2) = p_deciles;
end

20
matlab/variance_decomposition_mc_analysis.m
View File

@ -63,11 +63,11 @@ end
name = [ var '.' exo ];
if isfield(oo_, [ TYPE 'TheoreticalMoments'])
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments;'])
temporary_structure = oo_.([TYPE, 'TheoreticalMoments']);
if isfield(temporary_structure,'dsge')
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge;'])
temporary_structure = oo_.([TYPE, 'TheoreticalMoments']).dsge;
if isfield(temporary_structure,'VarianceDecomposition')
eval(['temporary_structure = oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.Mean;'])
temporary_structure = oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.Mean;
if isfield(temporary_structure,name)
% Nothing to do.
return
@ -110,12 +110,12 @@ else
posterior_moments(tmp,0,mh_conf_sig);
end
end
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.Mean.' name ' = p_mean;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.Median.' name ' = p_median;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.Variance.' name ' = p_var;']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.HPDinf.' name ' = hpd_interval(1);']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.HPDsup.' name ' = hpd_interval(2);']);
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.deciles.' name ' = p_deciles;']);
oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.Mean.(var).(exo) = p_mean;
oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.Median.(var).(exo) = p_median;
oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.Variance.(var).(exo) = p_var;
oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.HPDinf.(var).(exo) = hpd_interval(1);
oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.HPDsup.(var).(exo) = hpd_interval(2);
oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.deciles.(var).(exo) = p_deciles;
if options_.estimation.moments_posterior_density.indicator
eval(['oo_.' TYPE 'TheoreticalMoments.dsge.VarianceDecomposition.density.' name ' = density;']);
oo_.([TYPE, 'TheoreticalMoments']).dsge.VarianceDecomposition.density.(var).(exo) = density;
end